METHODS: A retrospective audit of heart transplant recipients (n = 87) treated with tacrolimus was performed. Relevant data were collected from the time of transplant to discharge. The concordance of tacrolimus dosing and monitoring according to hospital guidelines was assessed. The observed and software-predicted tacrolimus concentrations (n = 931) were compared for the first 3 weeks of oral immediate-release tacrolimus (Prograf) therapy, and the predictive performance (bias and imprecision) of the software was evaluated.

RESULTS: The majority (96%) of initial oral tacrolimus doses were guideline concordant. Most initial intravenous doses (93%) were lower than the guideline recommendations. Overall, 36% of initial tacrolimus doses were administered to transplant recipients with an estimated glomerular filtration rate of <60 mL/min/1.73 m despite recommendations to delay the commencement of therapy. Of the tacrolimus concentrations collected during oral therapy (n = 1498), 25% were trough concentrations obtained at steady-state. The software displayed acceptable predictions of tacrolimus concentration from day 12 (bias: -6%; 95%confidence interval, -11.8 to 2.5; imprecision: 16%; 95% confidence interval, 8.7-24.3) of therapy.

METHODS: Data from heart transplant recipients (n = 87) administered the oral immediate-release formulation of tacrolimus (Prograf®) were collected. Routine drug monitoring data, principally trough concentrations, were used for model building (n = 1099). A published tacrolimus model was used to inform the estimation of Ka , V2 /F, Q/F and V3 /F. The effect of concomitant azole antifungal use on tacrolimus CL/F was quantified. Fat-free mass was implemented as a covariate on CL/F, V2 /F, V3 /F and Q/F on an allometry scale. Subsequently, stepwise covariate modelling was performed. Significant covariates influencing tacrolimus CL/F were included in the final model. Robustness of the final model was confirmed using prediction-corrected visual predictive check (pcVPC). The final model was externally evaluated for prediction of tacrolimus concentrations of the fourth dosing occasion (n = 87) from one to three prior dosing occasions.

METHODS: Medical records of renal transplant patients at Penang General Hospital were retrospectively analyzed. A time-dissociated PKPD model with covariate effects was developed using NONMEM to evaluate renal graft function response, quantified as estimated glomerular filtration rate (eGFR), toward the cyclosporine cumulative exposure (area under the concentration-time curve). The final model was integrated into a tool to predict the potential outcome. Individual eGFR predictions were evaluated based on the clinical response recorded as acute rejection/nephrotoxicity events.

RESULTS: A total of 1256 eGFR readings with 2473 drug concentrations were obtained from 107 renal transplant patients receiving cyclosporine. An Emax drug effect with a linear drug toxicity model best described the data. The baseline renal graft level (E0), maximum effect (Emax), area under the concentration-time curve achieving 50% of the maximum effect, and nephrotoxicity slope were estimated as 12.9 mL·min-1·1.73 m-2, 50.7 mL·min-1·1.73 m-2, 1740 ng·h·mL-1, and 0.00033, respectively. The hemoglobin level was identified as a significant covariate affecting the E0. The model discerned acute rejection from nephrotoxicity in 19/24 cases.